By Nilesh Jahagirdar Artificial Intelligence (AI) has been prevalent in almost every business sector. However, in recent years, technology has burst into the healthcare landscape, propelling innovations and showcasing the potential to support medical practitioners and patients. From early disease diagnosis, drug discovery and trials, and precision in patient monitoring to self-care, AI algorithms have augmented the expertise of healthcare providers. According to the stats – AI expenditure in India is estimated to reach $11.78 bn by 2025, expected to add $1 trillion to the Indian economy by 2035. The new-age technology is dominating the healthcare industry so much that it's being referred to as the new nervous system.

We are surrounded by AI in our daily life whether it is the'Siri', 'Alexa', or the Google search engine. We have certainly come a long way from the'Turing test' in the 1950s, wherein the intelligent behaviour of computers was conceptualized leading to the present-day AI. The use of AI in Medicine (AIM) gained traction in the past decade and has met with both excitement in the scope of its use and also trepidation fearing the loss of the human element in the Art and Science of Medicine. Similar, to various subfields of Medicine the AI has its subfields of Machine learning (ML), Deep learning (DL) with Artificial Neural Network (ANN), Natural Language Processing (NLP), Computer Vision (CV). The use of AI in healthcare was slow to take off when compared to the non-medical commercial applications.

With the onset of the internet, websites and mobile apps, technology plays a huge role in aiding weight loss and staying fit. When it comes to losing weight, choosing which program is best for you and your body can be challenging. There is no one-size-fits-all diet or weight loss program, and most aren't explicitly tailored to you. Artificial Intelligence will be the future of weight loss and, more importantly, a more effective means of losing weight. Traditional weight-loss programs are flawed. Mainstream weight loss programs are created for a general demographic rather than for specific individuals, albeit with some modifications.

Washington: Researchers believe that developing cutting-edge artificial intelligence (AI) that can quickly and accurately identify lung diseases like pneumonia and tuberculosis could relieve the strain that winter months place on hospitals. Tuberculosis and pneumonia - potentially serious infections which mainly affect the lungs -often require a combination of different diagnostic tests,- such as CT scans, blood tests, X-rays, and ultrasounds. These tests can be expensive, with often lengthy waiting times for results. Developed by UWS, the revolutionary technology - originally created to quickly detect Covid-19 from X-ray images - has been proven to automatically identify a range of different lung diseases in a matter of minutes, with around 98 per cent accuracy. UWS researcher Professor Naeem Ramzan said: "Systems such as this could prove to be crucial for busy medical teams worldwide."

We aim to provide every individual a world class spectrum coaching by infusing top athletes and science professionals with artificial intelligence.

Representative image San Francisco: The US space agency has collaborated with Google to help local governments improve their monitoring and prediction of air quality. NASA and Google will develop advanced machine learning-based algorithms that link space data with Google Earth Engine data streams to generate high-resolution air quality maps in near real-time. "We're thrilled about our partnership with NASA to make daily air quality more actionable at a local level," said Rebecca Moore, director at Google Earth, Earth Engine and Outreach at Google. The results will create city-scale, near real-time estimation and forecasting of harmful pollutants, such as nitrogen dioxide and fine particulate matter. Google has incorporated two new NASA data sets into the Earth Engine Catalogue that are automatically updated daily.

AI has the potential to transform multiple aspects of patient care, administrative processes, payments and pharmaceutical organizations. There are several research studies suggesting that AI can perform equal to or even better than humans at key healthcare tasks, such as diagnosis avoiding some simple human errors. Presently, algorithms are already outperforming in radiology at detecting malignant tumours and helping researchers how to construct cohorts for costly clinical trials. The complexity of the disease and disease management means there is a high chance that arti1cial intelligence (AI) will increasingly be applied in the field. Multiple AI is already being employed by the payees as well as the providers of care, and life sciences companies.

New Delhi: Metaverse, the new buzzword amongst healthcare, a collective virtual shared space is no more a mystery box. This new emerging technology which is more prominent in the cryptocurrency market and gaming segment is now slowly proliferating in the healthcare domain. Some of the big hospitals are already adapting the digital virtual space of'metaverse'. ETHealthWorld explores what does this new technology'really' mean for healthcare? How will this technology make transformational changes, break the physical rules of the real world and redefine the future of the health domain.

By Gaurav Singh The technology has been evolving at a breaking-neck speed and has transformed how consumers interact with brands. Artificial intelligence is being actively used to streamline processes. In addition to chat, conversational AI and voice-activated chatbots powered by AI are emerging as alternate support systems that can simplify the complexities of human speech. Artificial intelligence (AI) techniques that allow machines to learn with minimal human supervision have emerged due to the exponential rise in computing power and data storage. Conversational AI (artificial intelligence) refers to systems that can "communicate" with humans, such as virtual assistants and chatbots (e.g., answer questions).

AI can analyze large amounts of data in order to identify patterns and hidden correlations, which would otherwise take humans considerably longer to comprehend and decipher. It can also be fed with a wide range of variables, which gives the engine more flexibility in its analysis. AI is revolutionising the overall healthcare landscape Automating healthcare is then, perhaps, a result of this changing healthcare landscape and the growing use and rapid adoption of technology. The healthcare sector is experiencing a dramatic shift in how goods and services are delivered. There are several driving factors in this transition, including a shift away from treating shorter episodes of illness towards a greater focus on long-term wellness and prevention. In addition consumers and patients alike show the deviation from and changing expectations.